DebugIT

In about half a century of antibiotic use, unexpected new challenges have come to light: fast emergence of resistances among pathogens, misuse and overuse of antibiotics; direct and indirect related costs. Antimicrobial resistance results in escalating healthcare costs, increased morbidity and mortality and the emergence or reemergence of potentially untreatable pathogens.

In this context of infectious diseases DebugIT project will (1) detect patient safety issues, (2) learn how to prevent them and (3) actually prevent them in clinical cases. Harmful patterns and trends using clinical and operational information from Clinical Information Systems (CIS) will be detect. This will be done through the 'view' of a virtualised Clinical Data Re-pository (CDR), featuring, transparent access to the original CIS and/or collection and aggregation of data in a local store. Text, image and structured data mining on individual patients as well as on populations will learn us informational and temporal patterns of patient harm.

This knowledge will be fed into a Medical Knowledge Repository and mixed with knowledge coming from external sources (for example guidelines and evidences). After editing and validating, this knowledge will be used by a decision support and monitoring tool in the clinical environment to prevent patient safety issues and report on it.

Outcomes and benefits, both clinical and economical will be measured and reported on. Innovation within this project lays in the virtualisation of Clinical Data Repository through ontology mediation, the advanced mining techniques, the reasoning engine and the consolidation of all these techniques in a comprehensive but open framework. This framework will be implemented, focused on infectious diseases, but will be applicable for all sorts of clinical cases in the future.

For further information, please visit:
http://www.debugit.eu

Project co-ordinator:
Agfa HealthCare (Belgium)

Partners:

  • empirica
  • Gama Sofia Ltd.
  • Institut National de la Santé et de Recherche Medicale
  • Internetový Pristup Ke Zdravotním Informacím Pacienta
  • Linköping University
  • Technological Educational Institute of Lamia
  • University College London
  • University Hospital of Geneva
  • University Medical Center Freiburg
  • University of Geneva

Timetable: from 01/2008 – to 12/2011

Total cost: €8.364.796

EC funding: €6.414.915

Programme Acronym: FP7-ICT

Subprogramme Area: Advanced ICT for risk assessment and patient safety

Contract type: Collaborative project (generic)


Related news article:

Most Popular Now

Early Warning System for Intensive Care …

Life-threatening situations occur time and again in an intensive care unit. To make sure that doctors can intervene in time, a team at the German Heart Center Berlin (DHZB) has...

Philips Partners with Orbita to Develop …

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Orbita Inc., an innovative provider of conversational artificial intelligence (AI) solutions for healthcare, announced a partnership agreement...

CliniSys Group Creates Single Brand for …

CliniSys Group has created a single brand for its businesses in the UK and Europe, with a refreshed logo and a new website. The move creates a unified identity for CliniSys...

East Lancashire Signs Deal for Early War…

Thousands of NHS professionals across five hospitals in East Lancashire are to benefit from early warning technology that will help them detect and swiftly respond to deteriorating patients in need...

FDA Grants Oxehealth Vital Signs De Novo…

Oxehealth has announced another world first after the US Food and Drug Administration granted a De Novo clearance for its Oxehealth Vital Signs product, which is incorporated into Oxevision, the...

Telemedicine Improves Access to High-Qua…

The American Academy of Sleep Medicine recently published an update on the use of telemedicine for the diagnosis and treatment of sleep disorders to reflect lessons learned from the transition...

Philips and NHS Implement the First Regi…

Royal Philips (NYSE: PHG, AEX: PHIA), announced it has supported the NHS' Cheshire and Merseyside consortium [1] to become the first regional hub supplying the United Kingdom's National COVID-19 Chest...

AI could Crack the Language of Cancer an…

Powerful algorithms used by Netflix, Amazon and Facebook can 'predict' the biological language of cancer and neurodegenerative diseases like Alzheimer's, scientists have found.

DMEA 2021: Digital Health. 100 % Virtual…

7 - 11 June 2021, Berlin, Germany. An entire week dominated by digital healthcare! With that in mind, early in June DMEA 2021 will be kicking off with a wide range...

X-Rays Combined with AI Offer Fast Diagn…

X-rays, first used clinically in the late 1890s, could be a leading-edge diagnostic tool for COVID-19 patients with the help of artificial intelligence, according to a team of researchers in...

Predicting COVID-19 Outbreaks with Cell …

Mobility tracking using cell phone data showing greater movement of people is a strong predictor of increased rates of COVID-19, according to new data in CMAJ (Canadian Medical Association Journal).